Presentation "Spanish Resources in Trendminer Project"

Slides used in Course "Combining Language and Semantic Web Techonologies" held in UNED, January 21-22, 2015.
The talk is about the challenges in understanding health related natural language and the work done in TrendMiner European Project.

9.
Level 1: Anatomical main group (1 letter)
Level 2: Therapeutic main group (2 digits)
Level 3: Pharmacological main group (1 letter)
Level 4: Chemical main group (1 letter)
Level 5: Active substance main group (2 digits)
ATC is a system of alphanumeric codes developed by the WHO for the classification of
drugs and other medical products
ATC Structure
(2) Integrated existing semantic domain resources
RESOURCES

23.
1. Distant-supervision method using the database on a collection
of 84,000 messages in order to extract the relations between
drugs and their effects (instances of DB are positive examples)
OTHER METHODS TO EXTRACT DRUG-EFFECT RELATIONS

24.
2. To classify the relation instances, we used a kernel method
based only on shallow linguistic information of the
sentences.
3. Regarding Relation Extraction of drugs and their effects, the
distant supervision approach achieved a recall of 0.59 and a
precision of 0.48
OTHER METHODS TO EXTRACT DRUG-EFFECT RELATIONS